In computer or data processing environments, it is desirable that all devices in the environment perform well. However, it may be very difficult to determine what “performing well” means for a particular device. Performance issues may be related to the device itself or to the ability of the attached system(s) to exploit device capabilities. Moreover, it may be very difficult to monitor performance and analyze various factors which might point to a degradation in performance. For example, in a data storage device, such as a tape drive, there are a large number of factors which can affect the performance of the device and many of them are not readily available to be analyzed.
Currently, analysis, if it is performed at all, is performed by an external system which may read very limited pieces of information and then create a statistical model of the device. However, the information typically provided by a device might not be sufficient to accurately determine device performance or related underlying causes for any unrealized performance. Moreover, the information used by the modeling system may not be consistent from one device to another of the same model or from one operating environment to another. Additionally, such a modeling system requires extensive tuning to be effective and there may not be a satisfactory method to validate the model.
Consequently, a need remains for a reliable, consistent and easy to use method to: determine the effective performance of a device, such as a tape drive; indicate degradation in performance and determine the cause of such degradation; and, identify any trends which might be useful as predictive failure indicators. It is further desirable that such a method be valid across a family of devices.